Ia & Se

Artificial Intelligence and Software Engineering: Status and Future Trends
Jörg Rech, Klaus-Dieter Althoff
The disciplines of Artificial Intelligence and Software Engineering have many commonalities. Both deal with modeling real world objects from the real world like business processes, expert knowledge, or process models. This article gives a short overview about these disciplines anddescribes some current research topics against the background of common points of contact.

1 Introduction
During the last decades the disciplines of Artificial Intelligence (AI) and Software Engineering (SE) have developed separately without much exchange of research results. In AI we researched techniques for the computations that made it possible to perceive, reason, and act. Research in SE wasconcerned with supporting human beings to develop better software faster. Today, several research directions of both disciplines come closer together and are beginning to build new research areas. Software Agents play an important role as research objects in Distributed AI (DAI) as well as in agentoriented software engineering (AOSE). Knowledge-Based Systems (KBS) are being investigated for learningsoftware organizations (LSO) as well as knowledge engineering. Ambient Intelligence (AmI) is a new research area for distributed, non-intrusive, and intelligent software systems both from the direction of how to build these systems as well as how to design the collaboration between ambient systems. Last but not least, Computational Intelligence (CI) plays an important role in research aboutsoftware analysis or project management as well as knowledge discovery in databases or machine learning. Furthermore, in the last five to ten years several books, journals, and conferences have focused on the intersection between AI and SE. The international conference and associated journal Automated Software Engineering (ASE) presents research about formal and autonomic approaches to support SE [2].Similar topics with a stronger focus on KBS and knowledge management are published in the international conference and associated journal of Software Engineering and Knowledge Engineering (IJSEKE) [1]. In this paper, we give a short overview about the status and future trends in the intersection between AI and SE. We focus on the topics software agents, KBS, AmI, and CI as the areas covered by thecontributions of this special issue. In Section 2 we describe the disciplines AI and SE. The focused topics are described in more detail in Section 3. Finally, in Section 4 we give an outlook for the next years and present new challenges for both disciplines.

Aspects of Artificial Intelligence
There is a general agreement in the AI community that the discipline of AI was born at the Dartmouthconference in 1956. According to Winston [81] “AI is the study of the computations that make it possible to perceive, reason, and act”. Wachsmuth [78] assumes this definition and points out that, “AI differs from most of psychology because of its greater emphasis on computation, and it differs from most of computer science because of its greater emphasis on perception, reasoning, and action”. As afield of academic study, many AI researchers reach to understand intelligence by becoming able to produce effects of intelligence: intelligent behavior. One element in AI’s methodology is that progress is sought by building systems that perform: synthesis before analysis [78]. “Systems are good science”, as Hendler said [34]. Or more drastically by Wachsmuth [78]: “it is not the aim of AI to buildintelligent machines having understood natural intelligence, but to understand natural intelligence by building intelligent machines”. Even more strikingly Aaron Sloman puts it this way (by citing his colleague Russel Beale): "AI can be defined as the attempt to get real machines to behave like the ones in the movies”. In addition, he points out that AI has two main strands, a scientific strand...